US 12,366,949 B2
Intelligent people-centric predictions in a collaborative environment
Michael Colagrosso, Boulder, CO (US); and Michael Procopio, Arvada, CO (US)
Assigned to Google LLC, Mountain View, CA (US)
Filed by Google LLC, Mountain View, CA (US)
Filed on Jun. 27, 2022, as Appl. No. 17/850,652.
Application 17/850,652 is a continuation of application No. 15/841,185, filed on Dec. 13, 2017, granted, now 11,372,522.
Prior Publication US 2022/0391051 A1, Dec. 8, 2022
Int. Cl. G06F 3/0482 (2013.01); G06F 16/176 (2019.01); G06F 16/93 (2019.01); G06F 40/166 (2020.01); G06N 5/022 (2023.01); G06N 20/00 (2019.01); G06Q 10/06 (2023.01); G06Q 10/101 (2023.01)
CPC G06F 3/0482 (2013.01) [G06F 16/176 (2019.01); G06F 16/93 (2019.01); G06F 40/166 (2020.01); G06N 5/022 (2013.01); G06N 20/00 (2019.01); G06Q 10/06 (2013.01); G06Q 10/101 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
generating, by a processing device, training data to train a machine learning model, wherein generating the training data comprises:
generating first training input, the first training input comprising information identifying one or more action attributes of a plurality of pending actions associated with a plurality of documents hosted by a cloud-based content management platform, the plurality of pending actions corresponding to invitations to a first user, from other users of the cloud-based content management platform, to perform operations associated with the plurality of documents; and
generating a first target output for the first training input, wherein the first target output indicates responses of the first user to the plurality of pending actions to the first user, from the other users, to perform the operations associated with the plurality of documents; and
training the machine learning model on the training data comprising (i) a set of training inputs comprising the first training input, and
(ii) a set of target outputs comprising the first target output, wherein training the machine learning model comprising adjusting one or more weights of the machine learning model based on the training data,
wherein the trained machine learning model is configured to generate an output identifying a probability of a first response of the first user to a new pending action from a second user for a document hosted by the cloud-based content management platform, and
wherein the output of the trained machine learning model is to cause a user interface (UI) component to be provided to a client device associated with the first user based on the probability of the first response, the UI component configured to receive the first response to the new pending action.